Download Waymo Open Dataset
Here are the datasets in the Waymo Open Dataset for downloading.
The Google Cloud Storage buckets below contain all of the files. This should facilitate programmatic downloading as well as allow easy access from Google Cloud APIs.
Motion Dataset
[new]v1.2.1 March 2024: Added camera embeddings data including 8 cameras with 360 degree coverage. Note this data provides embeddings only, not full images. - filesv1.2, March 2023: Added Lidar data and driveway labels. Increased the max number of map points in tf_examples to 30k and reduced sampling to 1.0m to increase map coverage, so the coverage equalizes that of the dataset in scenario proto format. - files
v1.2, March 2023: Added Lidar data and driveways. Increased the max number of map points in tf_examples to 30k and reduced sampling to 1.0m to increase map coverage, so the coverage equalizes that of the dataset in scenario proto format. - files
v1.1, August 2021: Added lane connections, lane boundaries, and lane neighbors. See Github page for technical specs. - files
v1.0, March 2021: Initial release - 103,354 segments with maps data - files
Perception Dataset
[new]March 2024: we fixed several small errors in the 3D semantic segmentation ground truth labels, especially for the class of motorcyclist. - v1.4.3 files - v2.0.1 filesv2.0.0, March 2023: Introduced the dataset in modular format, enabling users to selectively download only the components they need. - files
v1.4.2, March 2023: Added 3D map data as polylines or polygons. For 2D panoptic segmentation labels, added a mask to indicate pixels covered by multiple cameras. - files
v2.0.0, August 2023: Added the Perception object assets data - files
v2.0.0, March 2023: Introduced the dataset in modular format, enabling users to selectively download only the components they need. - file link same as abovev1.4.2, March 2023: Added 3D map data as polylines or polygons. For 2D panoptic segmentation labels, added a mask to indicate pixels covered by multiple cameras. - files
v1.4.1, December 2022: Improved the quality of the 2D video panoptic segmentation labels - files
v1.4.0, June 2022: Added 2D video panoptic segmentation labels - files
v1.3.2, May 2022: Improved the quality of the 3D semantic segmentation labels and 2D key point labels. Added a new field for the 3D Camera-Only Detection Challenge. - files
v1.3.1, April 2022: Updated the dataset for the 3D Camera-Only Detection Challenge. This version includes a new test set with 80 segments, and additional fields for training and validation - tar files, individual files
v1.3.0, March 2022: Added 3D semantic segmentation labels, 2D and 3D key points labels, and 2D-to-3D label correspondence labels - files
v1.2, March 2020: Added Test Set with 150 segments, plus 800 segments for domain adaptation across Training, Validation, and Test - tar files, individual files
v1.1, February 2020: Added camera labels for 900 segments - tar files, individual files
v1.0, August 2019: Initial release - tar files, individual files
Community Contributions
Causal Agents Labels
Released in 2022, by Google Brain and Waymo
Based on the Waymo Open Motion Dataset, the causal agent labels identify agents whose presence influences human drivers' behavior in any format. In addition to causal agent labels, the team also release perturbed copies of the Waymo Open Motion Dataset validation dataset, which serve as robustness benchmarks to aid the research community in building more reliable and safe models for motion forecasting.
Causal agent labels files, GitHub, and paper: "CausalAgents: A Robustness Benchmark for Motion Forecasting using Causal Relationships"
Scene Flow Labels
Released in 2021, by Google Brain and Waymo
The scene flow labels builds on Perception v1.2 of the Waymo Open Dataset. This release comprises supervised labels for each point cloud reflection with a direction and magnitude of motion at each time step. These labels are derived from tracked bounding boxes associated with labeled objects in the scene.
Scene flow labels files, and paper: "Scalable Scene Flow from Point Clouds in the Real World"
ROAD-Waymo Dataset
Released in 2023, by Oxford Brookes University
The ROAD-Waymo dataset builds on the Waymo Open Dataset, by adding the following annotations: action labels (turning-right, moving-away, etc.), agent type labels (pedestrians, large-vehicle, etc.), semantic location labels (in vehicle lane, in right pavement, etc.). The dataset is used in the Second Workshop & Challenge on Event Detection for Situation Awareness in Autonomous Driving at ICCV'23.